Summary

Stirred tanks are probably the most used apparatus in the process industry, e.g., used for extraction processes involving immiscible liquid-liquid systems. In this case, the two phases must be separated in a downstream settler before further processing. The efficient operation of extractive liquid-liquid systems in these mixer-settler units struggles from the contrary requirements of the two unit operations. Tiny droplets and a narrow drop size distribution are ideal for interfacial mass transfer in the stirred tank. In contrast, larger drops are beneficial for fast phase separation in the settler. Parameters influencing this dilemma are, i.a., stirring speed, dispersed phase fraction, flow rates, and residence times. The project aims for a robust and dynamic process control concept based on a suitable system model to tackle this challenge. The novel optimization approach of this project consists of identifying the potential of the dynamic operation of mixer-settlers based on a controlled variation of flow rates and stirrer speed. The first project period focuses on the stirred tank. In the beginning, material systems of a polar continuous water phase and a nonpolar dispersed organic phase with various physical properties are characterized in detail regarding their coalescence and mass transfer behavior (WP 1). For the development of system models and process control, fast and reproducible inline-measurement techniques for the drop size distributions and the mass transfer are established to get experimental data for the simulation and modeling of the process in nearly real-time (WP 2). First, a model for process control is developed for the batch stirred tank (WP 3). Drop size distributions and mass transfer rates are measured for specific process settings. Population balance equation simulations are performed to determine the sub-model parameters for breakage and coalescence. The sensitivity of these parameters is analyzed under dynamic conditions. Online optimal experimental design techniques are used to identify suitable process modeling and control parameters. The developed model-based process control is then validated and extended using experimental data from a continuous stirred tank for accounting for dynamic changes and perturbations of flow rates and concentrations at the tank inlet (WP 4). This strategy includes Model Predictive Control as well as classic control approaches. In the second funding period, the control concept is extended to the complete process chain of a mixer-settler unit. Developing a suitable process control for an optimum between tiny droplets for mass transfer and large droplets allowing fast separation will be essential.